Cities are attempting to reduce the number of cars on the road and improve commuting times by creating high occupancy vehicle (HOV) lanes or high occupancy tolling (HOT) lanes. For example, certain highways may have lanes dedicated for cars carrying two or more persons or three or more persons. However, some cars having only a single person may attempt to drive in these lanes creating extra congestion, which defeats the purpose of the HOV/HOT lanes.
Currently, to enforce traffic rules associated with the HOV/HOT lanes law enforcement officers must be dispatched to a side of the HOV or HOT lanes to visually examine incoming or passing vehicles. Using law enforcement officers for counting people in cars of an HOV/HOT lane may be a poor utilization of the law enforcement officers. In other words, deploying law enforcement officers to regulate the HOV/HOT lanes is expensive and inefficient.
Some facial detection methods have attempted to automate detection of people in vehicles for the HOV or HOT lanes. However, due to varying conditions or varying image quality, the currently deployed methods may not be consistent or accurate in detecting people in a vehicle.